Unimodal Thompson Sampling for Graph-Structured Arms

We study, to the best of our knowledge, the first Bayesian algorithm for unimodal Multi-Armed Bandit (MAB) problems with graph structure. In this setting, each arm corresponds to a node of a graph and each edge provides a relationship, unknown to the learner, between two nodes in terms of expected reward. Furthermore, for any node of the graph there is a path leading to the unique node providing the maximum expected reward, along which the expected reward is monotonically increasing. Previous results on this setting describe the behavior of frequentist MAB algorithms. In our paper, we design a Thompson Sampling-based algorithm whose asymptotic pseudo-regret matches the lower bound for the considered setting. We show that -as it happens in a wide number of scenarios- Bayesian MAB algorithms dramatically outperform frequentist ones. In particular, we provide a thorough experimental evaluation of the performance of our and state-of-the-art algorithms as the properties of the graph vary

Truthful Learning Mechanisms for Multi-Slot Sponsored Search Auctions with Externalities

Sponsored search auctions constitute one of the most successful applications of microeconomic mechanisms. In mechanism design, auctions are usually designed to incentivize advertisers to bid their truthful valuations and to assure both the advertisers and the auctioneer a non-negative utility. Nonetheless, in sponsored search auctions, the click-through-rates (CTRs) of the advertisers are often unknown to the auctioneer and thus standard truthful mechanisms cannot be directly applied and must be paired with an effective learning algorithm for the estimation of the CTRs. This introduces the critical problem of designing a learning mechanism able to estimate the CTRs at the same time as implementing a truthful mechanism with a revenue loss as small as possible compared to an optimal mechanism designed with the true CTRs. Previous work showed that, when dominant-strategy truthfulness is adopted, in single-slot auctions the problem can be solved using suitable exploration-exploitation mechanisms able to achieve a per-step regret (over the auctioneer's revenue) of order $O(T^{-1/3})$ (where T is the number of times the auction is repeated). It is also known that, when truthfulness in expectation is adopted, a per-step regret (over the social welfare) of order $O(T^{-1/2})$ can be obtained. In this paper we extend the results known in the literature to the case of multi-slot auctions. In this case, a model of the user is needed to characterize how the advertisers' valuations change over the slots. We adopt the cascade model that is the most famous model in the literature for sponsored search auctions. We prove a number of novel upper bounds and lower bounds both on the auctioneer's revenue loss and social welfare w.r.t. to the VCG auction and we report numerical simulations investigating the accuracy of the bounds in predicting the dependency of the regret on the auction parameters

The Wall-Jet Region of a Turbulent Jet Impinging on Smooth and Rough Plates

The study reports direct numerical simulations of a turbulent jet impinging onto smooth and rough surfaces at Reynolds number Re = 10,000 (based on the jet mean bulk velocity and diameter). Surface roughness is included in the simulations using an immersed boundary method. The deflection of the flow after jet impingement generates a radial wall-jet that develops parallel to the mean plate surface. The wall-jet is structured into an inner and an outer layer that, in the limit of infinite local Reynolds number, resemble a turbulent boundary layer and a free-shear flow. The investigation assesses the self-similar character of the mean radial velocity and Reynolds stresses profiles scaled by inner and outer layer units for varying size of the roughness topography. Namely the usual viscous units $u_{\tau}$ and $\delta_{\upsilon}$ are used as inner layer scales, while the maximum radial velocity $u_{m}$ and its wall-normal location $z_{m}$ are used as outer layer scales. It is shown that the self-similarity of the mean radial velocity profiles scaled by outer layer units is marginally affected by the span of roughness topographies investigated, as outer layer velocity and length reference scales do not show a significantly modified behavior when surface roughness is considered. On the other hand, the mean radial velocity profiles scaled by inner layer units show a considerable scatter, as the roughness sub-layer determined by the considered roughness topographies extends up to the outer layer of the wall-jet. Nevertheless, the similar character of the velocity profiles appears to be conserved despite the profound impact of surface roughness

A Truthful Learning Mechanism for Contextual Multi--Slot Sponsored Search Auctions with Externalities

International audienceSponsored search auctions constitute one of the most successful applications of \emph{microeconomic mechanisms}. In mechanism design, auctions are usually designed to incentivize advertisers to bid their truthful valuations and, at the same time, to assure both the advertisers and the auctioneer a non--negative utility. Nonetheless, in sponsored search auctions, the click--through--rates (CTRs) of the advertisers are often unknown to the auctioneer and thus standard incentive compatible mechanisms cannot be directly applied and must be paired with an effective learning algorithm for the estimation of the CTRs. This introduces the critical problem of designing a learning mechanism able to estimate the CTRs as the same time as implementing a truthful mechanism with a revenue loss as small as possible compared to an optimal mechanism designed with the true CTRs. Previous works showed that in single--slot auctions the problem can be solved using a suitable exploration--exploitation mechanism able to achieve a per--step regret of order $O(T^{-1/3})$ (where $T$ is the number of times the auction is repeated). In this paper we extend these results to the general case of contextual multi--slot auctions with position-- and ad--dependent externalities. In particular, we prove novel upper--bounds on the revenue loss w.r.t. to a VCG auction and we report numerical simulations investigating their accuracy in predicting the dependency of the regret on the number of rounds $T$, the number of slots $K$, and the number of advertisements $n$

Connection between inelastic x-ray scattering and complementary x-ray spectroscopies: probing excitons at Al K and L1 edges of α\alpha-Al2_2O3_3

We present an ab initio study of core excitations at the aluminum K and L1 edges in ${\alpha}$-Al2O3 within an all-electron many-body perturbation theory (MBPT) framework. Calculated XAS reveals excellent agreement with experiments, highlighting the dipole-forbidden nature of the pre-peak, which in experiments is enabled by sp mixing due to atomic vibrations. Non-resonant inelastic X-ray scattering (NRIXS) is employed to go beyond the dipole approximation and probe transition channels with s, p, and d character, enhancing multipole transitions that contribute to the pre-peak. The RIXS spectra at K and L1 edges are remarkably similar, opening the way to soft X-ray RIXS experiments to probe semi-core s states. The RIXS calculations reveal two distinct regimes based on the behavior with incoming photon energy ($\omega_1$). For $\omega_1$ in resonance with the XAS threshold, we observe Raman-like behavior, where the RIXS spectra show significant dependence on $\omega_1$ , reflecting the coupling between absorption and emission processes. For higher $\omega_1$ , above the XAS threshold, the study reveals fluorescence features that appear at constant emission energy, and can be explained via X-ray emission spectroscopy (XES)

Servicio de geoposicionamiento cooperativo para dispositivos móviles

La motivación de desarrollar este proyecto surge de una necesidad real. En determinados contextos un usuario puede estar interesado en compartir su ubicación con sus contactos. De esta idea surge este proyecto, en el que se desarrolla una aplicación para Android (extensible a otras plataformas móviles en el futuro) que muestra al usuario, sobre mapas personalizados, su propia ubicación y la de sus amigos, siempre que estos hayan decidido compartirla. Google Latitude ofrece una funcionalidad similar a la perseguida pero tiene algunas carencias. Se ejecuta sobre Google Maps que, aun siendo personalizable y muy potente, no permite utilizar mapas diferentes a los proporcionados. No actualiza la posición de los contactos en tiempo real, sino sólo cuando se cumplen determinadas circunstancias. Esto hace que no sea útil en situaciones donde la tasa de refresco y la información actualizada es importante. La aplicación debe: - Permitir a los usuarios conocer su ubicación y la de sus contactos en mapas personalizados. - Recibir actualizaciones frecuentes de las posiciones de los contactos. - Ser fácil de utilizar, automatizando la mayor parte de procesos y requiriendo la mínima interacción con el usuario. - Ser potente y flexible, y que pueda ser adaptada a un elevado número de contextos. Partiendo de estas consideraciones, se desarrolla la aplicación que emplea un número elevado de las opciones que Android ofrece a los desarrolladores. Además está respaldada por una conexión al servidor, alojado en Google App Engine.Ingeniería en Informátic

Evaluation of an e-learning device for workers' compulsory training: an example of collaboration between university and company

Abstract In this article, we present the collaboration between the Quality, Hygiene, Security and Training department of the service provider of the Coop-branded cooperatives and the Human Sciences and Education Department of the University of Perugia, the objective of which was compulsory training in the fields of Job Security and Food Hygiene, provided by the company in e-learning, and addressing the employees of several cooperatives operating in the largescale organised distribution sector. The collaboration contemplates two steps. The first one consisted of the certification of compliance according to certain quality criteria. Course evaluation and certification were therefore assigned to an external institution that researches these subjects and thus was able to provide the training governance team with matter for reflection on the implemented training path, also indicating some potential aspects that needed to be further developed. The second step consisted of a wide-ranging, articulated empirical research that, on the one hand, enabled the university to cast light on a phenomenon that has been studied little or not at all from an educational viewpoint and, on the other, has enabled the Consorzio Interprovinciale di Servizi-Quality, Hygiene, Security and Training department (CIS-QuISF) to enhance its professional perspective and the e-learning mode to gain increasing recognition

A Cooperative Negotiation Protocol for Physiological Model Combination

The global model of a complex phenomenon can emerge from the cooperative negotiation of agents embedding local partial models of the phenomenon. We adopted this approach to model complex physiological phenomena, such as those related to the metabolism of glucose-insulin and to the determination of the heart rate (pacing). In this paper we formally describe and analyze the properties of a cooperative negotiation protocol we developed to allow the agents to produce a global coherent model of a physiological phenomenon. We concentrate on the study of the conditions under which an agreement is guaranteed to be reached. We also show details of an application concerning the pacing problem